Energy-based decision engine for household human activity recognition

Anastasios Vafeiadis, Thanasis Vafeiadis, Stelios Zikos, Stelios Krinidis, Konstantinos Votis, Dimitrios Giakoumis, Dimosthenis Ioannidis, Dimitrios Tzovaras, Liming Chen, Raouf Hamzaoui

Research output: Contribution to conferencePaper

1 Citation (Scopus)

Abstract

We propose a framework for energy-based human activity recognition in a household environment. We apply machine learning techniques to infer the state of household appliances from their energy consumption data and use rule- based scenarios that exploit these states to detect human activity. Our decision engine achieved a 99.1% accuracy for real-world data collected in the kitchens of two smart homes.
Original languageEnglish
Pages704-709
DOIs
Publication statusPublished - Mar 2018
Event2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) - Athens
Duration: 19 Mar 201823 Mar 2018

Conference

Conference2018 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops)
Period19/03/1823/03/18

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